Displaying 4 results from an estimated 4 matches for "johnlangford".
2015 Aug 22
3
sprintf error: "only 100 arguments allowed"
I'm trying to apply a function defined in the VW R docs, that attemps to
convert a data.table object to Vowpal Wabbit format. In the process i'm
getting the error in printf mentioned in the subject.
The original function is here:
https://github.com/JohnLangford/vowpal_wabbit/blob/master/R/dt2vw.R
Below there is a small example that reproduces the error. The function
works great with smaller (less than 100 columns), as shown.
Any suggestions of alternative methods to acomplish the same would be
great, but I'm basically asking, is there a reason for...
2015 Aug 26
1
sprintf error: "only 100 arguments allowed"
...t;> I'm trying to apply a function defined in the VW R docs, that attemps to
>> convert a data.table object to Vowpal Wabbit format. In the process i'm
>> getting the error in printf mentioned in the subject.
>> The original function is here:
>> https://github.com/JohnLangford/vowpal_wabbit/blob/master/R/dt2vw.R
>>
>>
>> Below there is a small example that reproduces the error. The function
>> works great with smaller (less than 100 columns), as shown.
>>
>> Any suggestions of alternative methods to acomplish the same would be
>>...
2015 Aug 25
0
sprintf error: "only 100 arguments allowed"
...Martin Bel wrote:
> I'm trying to apply a function defined in the VW R docs, that attemps to
> convert a data.table object to Vowpal Wabbit format. In the process i'm
> getting the error in printf mentioned in the subject.
> The original function is here:
> https://github.com/JohnLangford/vowpal_wabbit/blob/master/R/dt2vw.R
>
>
> Below there is a small example that reproduces the error. The function
> works great with smaller (less than 100 columns), as shown.
>
> Any suggestions of alternative methods to acomplish the same would be
> great, but I'm basicall...
2011 Sep 07
1
predictive modeling and extremely large data
Hi,
I am new to R and here is what I am doing in it now. I am using machine
learning technique (svm) to do predictive modeling. The data that I am using
is one that is bound to grow perpetually. what I want to know is, say, I fed
in a data set with 5000 data points to svm initially. The algorithm derives
a certain intelligence (i.e.,output) based on these 5000 data points. I
have an additional